Soft-Matrices Computation for Feature Selection on Traditional Malay Musical Instrument Sounds Dataset

Soft set theory proposed by Molodtsov is a new mathematical tool for dealing with the uncertain data. Soft set-based dimensionality reduction can be considered as a technique for feature selection. In this paper, we present an alternative technique for feature selection of traditional Malay musical instrument sounds dataset. The technique is based on matrices computation of multi-soft sets for dimensionality reduction. The dataset is taken from our previous work which consists of 1116 instances and 37 attributes of Malay Musical Instrument Sounds Dataset. The result shows that the obtained features of proposed technique are 35 out of 37 features.